Software development

Software development

When staff resort to copying data between spreadsheets, keeping shadow systems in Excel, or doing repetitive tasks that feel like they should be automated, something is wrong. These workarounds creep in gradually; a quick fix here, a temporary solution there, until suddenly your operations depend on a patchwork of manual processes. Workarounds rarely stay small. What begins as a simple spreadsheet to track information your CRM cannot handle eventually becomes a document that multiple team members depend on.

Manual database deployment means longer release times. Database specialists have to spend several working days prior to release writing and testing scripts which in itself leads to prolonged deployment cycles and less time for testing. As a result, applications are not released on time and customers are not receiving the latest updates and bug fixes. Manual work inevitably results in errors, which cause problems and bottlenecks.

DBmaestro is a database release automation solution that can blend the database delivery process seamlessly into your current DevOps ecosystem with minimal fuss, and without complex installation or maintenance. Its handy database pipeline builder allows you to package, verify, and deploy, and gives you the ability to pre-run the next release in a provisional environment to detect errors early. You get a zero-friction pipeline, which is often not the case with database delivery process.

To find the typical example, just observe an average stand-up meeting. The ones who talk more get all the attention. In her article, software engineer Priyanka Jain tells the story of two colleagues assigned the same task. One posted updates, asked questions, and collaborated loudly. The other stayed silent and shipped clean code. Both delivered. Yet only one was praised as a "great team player."

The main promise is isolation: a Docker container that works on an x86_64 Linux machine will work on any x86_64 Linux machine in the same way. Want to quickly set up PostgreSQL for testing? Just run docker run --name postgres -e POSTGRES_PASSWORD=postgres -p 5432:5432 -d --restart=unless-stopped postgres and wait a few seconds. Docker is great for deployment as well as production deployments, and it even supports Windows Server containers these days.

Microsoft's .NET Framework 3.5 development platform, which dates back to November 2007, is no longer included as an optional Windows component. Microsoft has changed its deployment model to standalone installer status for future Windows versions. In a bulletin published February 5, Microsoft said that beginning with Windows 11 Insider Preview Build 27965, .NET Framework 3.5 must be obtained as a standalone installer for applications that require it on newer major versions of Windows.

FreeBSD is a Unix-like operating system that is descended from the Berkeley Software Distribution. The first version of FreeBSD was released in 1993 and was developed from 386BSD, one of the first fully functional and free Unix clones on affordable hardware. Since its inception, FreeBSD has been the most widely used BSD-derived operating system. FreeBSD maintains a complete system: kernel, device drivers, userland utilities, and documentation.

If there's one thing I want you to take away from this article, it's this: testing harness is the most important thing for vibe-coding. Not prompt engineering, not fancy plugins, just constraining your AI outside AI toolchain. I'm calling it harness because it's not only tests. It's tests, types, linters, and any other automated checks you can put in place. The more you rely on AI, the more harness you need.

PF4J expects that your plugin code has a class that extends org.pf4j.Plugin interface. And for running and stopping the plugin, methods start() and stop() of this interface will be called. But our service is expected to have completely pure logic - without any side effects - we need to bring these two worlds together - Java impure plugins start/stop and Scala pure logic.

Project Genie, which is currently only available for Google's AI Ultra subscribers, uses AI to build virtual worlds. That sounds interesting, if not necessarily revolutionary. Videogame developers already model and build virtual worlds all the time. Project Genie's simple concept, though, belies the tech's potential impact. The new system, and the Genie 3 model behind it, have the potential to forever change how videogames are built and played.

Also: This Linux distro has one of the smartest security features I've seen (and I've tested dozens) However, that's not to say someone with minimal familiarity with the command line would fail with this distribution. For example, if you only need open-source software, NixOS could be a viable option. If, however, you need apps like Chrome, Slack, and Spotify, you might run into some frustration that will send you packing back to Ubuntu, Linux Mint, or Windows.

Databricks today announced the general availability of Lakebase on AWS, a new database architecture that separates compute and storage. The managed serverless Postgres service is designed to help organizations build faster without worrying about infrastructure management. When databases link compute and storage, every query must use the same CPU and memory resources. This can cause a single heavy query to affect all other operations. By separating compute and storage, resources automatically scale with the actual load.

The reason for this is Snap - a Linux application packaging format - creates a local Trash folder for each VS Code version, one that's separate from the system-managed Trash, according to a VS Code bug report dating back to November 11, 2024. Not only that, but Snap keeps older versions of VS Code after updates, potentially multiplying the number of local Trash folders and the trashed-but-not-deleted files therein. Emptying the system Trash folder doesn't affect the local instances.

Benevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about. Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We're also one of the first B Corporations in Canada, meaning we're as committed to purpose as we are to profits.

One thing I always do when I prompt a coding agent is to tell it to ask me any questions that it might have about what I've asked it to do. (I need to add this to my default system prompt...) And, holy mackerel, if it doesn't ask good questions. It almost always asks me things that I should have thought of myself.

Custom agents in GitHub Copilot are tailored versions of the Copilot coding agent that you can define once to follow your own workflows, coding conventions, and tool preferences. They act like specialized teammates that consistently apply your team's standards instead of you repeating the same instructions each time. You configure custom agents using Markdown-based agent profiles that specify prompts, tools, and behaviors.

This video course will teach you how to use Gemini CLI to bring Google's AI-powered coding assistance directly into your terminal. After you authenticate with your Google account, this tool will be ready to help you analyze code, identify bugs, and suggest fixes-all without leaving your familiar development environment. Imagine debugging code without switching between your console and browser, or picture getting instant explanations for unfamiliar projects.

Wasmer has released Wasmer 7, an upgrade of its WebAssembly runtime that introduces an experimental async API that enables full async support in Python. The update also brings support for dynamic linking to WASIX, broadening the platform's support for Python packages. Introduced January 30, Wasmer 7 introduces an experimental async API that offers first-class support for async functions in Python, unlocking powerful libraries such as SQLAlchemy and other Python packages that previously could not run, Wasmer said.

Industry professionals are realizing what's coming next, and it's well captured in a recent LinkedIn thread that says AI is moving on from being just a helper to a full-fledged co-developer - generating code, automating testing, managing whole workflows and even taking charge of every part of the CI/CD pipeline. Put simply, AI is transforming DevOps into a living ecosystem, one driven by close collaboration between human judgment and machine intelligence.

Creating your theme is the fun part. After you're done, the next step is to publish your theme so you - and others - can enjoy your creation! You'd think that publishing a VS Code extension is an easy process, but it's not. (Maybe I'm used to the ease of publishing npm packages and take registries for granted.) Anyway, you have to publish your theme in two places: Visual Studio Marketplace for VS Code users Open VSX for other text editors

Salesforce data migration sounds straightforward on paper. In practice, it almost never is. The system goes live, everyone gets access, and nothing seems obviously wrong at first. Then little questions start popping up. A report doesn't quite line up. A dashboard only makes sense after a few extra filters. Sales reps pull numbers into Excel just to feel sure. Before long, Salesforce is technically running, but confidence in the data hasn't caught up.